35 search results - page 1 / 7 » Genetic weighted k-means algorithm for clustering large-scal... |
AAAI
2008
13 years 7 months ago
2008
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...
BMCBI
2008
13 years 5 months ago
2008
Background: The traditional (unweighted) k-means is one of the most popular clustering methods for analyzing gene expression data. However, it suffers three major shortcomings. It...
IJCNN
2008
IEEE
13 years 11 months ago
2008
IEEE
—Normalization before clustering is often needed for proximity indices, such as Euclidian distance, which are sensitive to differences in the magnitude or scales of the attribute...
BMCBI
2007
13 years 5 months ago
2007
Background: Detecting groups of functionally related proteins from their amino acid sequence alone has been a long-standing challenge in computational genome research. Several clu...
ISMB
2000
13 years 6 months ago
2000
The immensevolumeof data resulting from DNAmicroarray experiments, accompaniedby an increase in the numberof publications discussing gene-related discoveries, presents a majordata...